AdaBagModel {MachineShop} | R Documentation |
Bagging with Classification Trees
Description
Fits the Bagging algorithm proposed by Breiman in 1996 using classification trees as single classifiers.
Usage
AdaBagModel(
mfinal = 100,
minsplit = 20,
minbucket = round(minsplit/3),
cp = 0.01,
maxcompete = 4,
maxsurrogate = 5,
usesurrogate = 2,
xval = 10,
surrogatestyle = 0,
maxdepth = 30
)
Arguments
mfinal |
number of trees to use. |
minsplit |
minimum number of observations that must exist in a node in order for a split to be attempted. |
minbucket |
minimum number of observations in any terminal node. |
cp |
complexity parameter. |
maxcompete |
number of competitor splits retained in the output. |
maxsurrogate |
number of surrogate splits retained in the output. |
usesurrogate |
how to use surrogates in the splitting process. |
xval |
number of cross-validations. |
surrogatestyle |
controls the selection of a best surrogate. |
maxdepth |
maximum depth of any node of the final tree, with the root node counted as depth 0. |
Details
- Response types:
factor
- Automatic tuning of grid parameters:
-
mfinal
,maxdepth
Further model details can be found in the source link below.
Value
MLModel
class object.
See Also
Examples
## Requires prior installation of suggested package adabag to run
fit(Species ~ ., data = iris, model = AdaBagModel(mfinal = 5))
[Package MachineShop version 3.7.0 Index]